'''simple docstring'''
import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class lowerCamelCase				(						lowerCamelCase  ,		unittest.TestCase       ):




  '''simple docstring'''



  lowerCAmelCase__      				=						BarthezTokenizer
  lowerCAmelCase__      				=						BarthezTokenizerFast
  lowerCAmelCase__      				=						True
  lowerCAmelCase__      				=						True






  def 			lowerCAmelCase__			(   self      :							Dict	)					->Optional[Any]:
        super().setUp()

        UpperCAmelCase_      =	BarthezTokenizerFast.from_pretrained('''moussaKam/mbarthez'''	)
        tokenizer.save_pretrained(self.tmpdirname	)
        tokenizer.save_pretrained(self.tmpdirname	,				legacy_format=UpperCAmelCase__	)
        UpperCAmelCase_      =	tokenizer






  def 			lowerCAmelCase__			(   self      :							List[Any]	)					->Any:
        UpperCAmelCase_      =	'''<pad>'''
        UpperCAmelCase_      =	1

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase__	)	,				UpperCAmelCase__	)
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase__	)	,				UpperCAmelCase__	)






  def 			lowerCAmelCase__			(   self      :							Optional[int]	)					->Any:
        UpperCAmelCase_      =	list(self.get_tokenizer().get_vocab().keys()	)

        self.assertEqual(vocab_keys[0]	,				'''<s>'''	)
        self.assertEqual(vocab_keys[1]	,				'''<pad>'''	)
        self.assertEqual(vocab_keys[-1]	,				'''<mask>'''	)
        self.assertEqual(len(UpperCAmelCase__	)	,				10_1122	)






  def 			lowerCAmelCase__			(   self      :							Union[str, Any]	)					->str:
        self.assertEqual(self.get_tokenizer().vocab_size	,				10_1122	)






  @require_torch
  def 			lowerCAmelCase__			(   self      :							Dict	)					->str:
        UpperCAmelCase_      =	['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
        UpperCAmelCase_      =	[0, 57, 3018, 7_0307, 91, 2]

        UpperCAmelCase_      =	self.tokenizer(
            UpperCAmelCase__	,				max_length=len(UpperCAmelCase__	)	,				padding=UpperCAmelCase__	,				truncation=UpperCAmelCase__	,				return_tensors='''pt'''	)
        self.assertIsInstance(UpperCAmelCase__	,				UpperCAmelCase__	)

        self.assertEqual((2, 6)	,				batch.input_ids.shape	)
        self.assertEqual((2, 6)	,				batch.attention_mask.shape	)
        UpperCAmelCase_      =	batch.input_ids.tolist()[0]
        self.assertListEqual(UpperCAmelCase__	,				UpperCAmelCase__	)






  def 			lowerCAmelCase__			(   self      :							int	)					->Tuple:


        if not self.test_rust_tokenizer:
              return

        UpperCAmelCase_      =	self.get_tokenizer()
        UpperCAmelCase_      =	self.get_rust_tokenizer()

        UpperCAmelCase_      =	'''I was born in 92000, and this is falsé.'''

        UpperCAmelCase_      =	tokenizer.tokenize(UpperCAmelCase__	)
        UpperCAmelCase_      =	rust_tokenizer.tokenize(UpperCAmelCase__	)
        self.assertListEqual(UpperCAmelCase__	,				UpperCAmelCase__	)

        UpperCAmelCase_      =	tokenizer.encode(UpperCAmelCase__	,				add_special_tokens=UpperCAmelCase__	)
        UpperCAmelCase_      =	rust_tokenizer.encode(UpperCAmelCase__	,				add_special_tokens=UpperCAmelCase__	)
        self.assertListEqual(UpperCAmelCase__	,				UpperCAmelCase__	)

        UpperCAmelCase_      =	self.get_rust_tokenizer()
        UpperCAmelCase_      =	tokenizer.encode(UpperCAmelCase__	)
        UpperCAmelCase_      =	rust_tokenizer.encode(UpperCAmelCase__	)
        self.assertListEqual(UpperCAmelCase__	,				UpperCAmelCase__	)






  @slow
  def 			lowerCAmelCase__			(   self      :							Tuple	)					->Union[str, Any]:
        UpperCAmelCase_      =	{'''input_ids''': [[0, 490, 1_4328, 4507, 354, 47, 4_3669, 95, 25, 7_8117, 2_0215, 1_9779, 190, 22, 400, 4, 3_5343, 8_0310, 603, 86, 2_4937, 105, 3_3438, 9_4762, 196, 3_9642, 7, 15, 1_5933, 173, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 1_0534, 87, 25, 66, 3358, 196, 5_5289, 8, 8_2961, 81, 2204, 7_5203, 7, 15, 763, 1_2956, 216, 178, 1_4328, 9595, 1377, 6_9693, 7, 448, 7_1021, 196, 1_8106, 1437, 1_3974, 108, 9083, 4, 4_9315, 7, 39, 86, 1326, 2793, 4_6333, 4, 448, 196, 7_4588, 7, 4_9315, 7, 39, 21, 822, 3_8470, 74, 21, 6_6723, 6_2480, 8, 2_2050, 5, 2]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
        # fmt: on

        # moussaKam/mbarthez is a french model. So we also use french texts.
        UpperCAmelCase_      =	[
            '''Le transformeur est un modèle d\'apprentissage profond introduit en 2017, '''
            '''utilisé principalement dans le domaine du traitement automatique des langues (TAL).''',
            '''À l\'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus '''
            '''pour gérer des données séquentielles, telles que le langage naturel, pour des tâches '''
            '''telles que la traduction et la synthèse de texte.''',
        ]

        self.tokenizer_integration_test_util(
            expected_encoding=UpperCAmelCase__	,				model_name='''moussaKam/mbarthez'''	,				revision='''c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'''	,				sequences=UpperCAmelCase__	,				)









import requests
from bsa import BeautifulSoup
def 							UpperCamelCase_(					_A :str = "AAPL"	)->		str:
			UpperCamelCase__       =							F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
			UpperCamelCase__       =							BeautifulSoup(requests.get(_A	).text					,  "html.parser"	)
			UpperCamelCase__       =							"My(6px) Pos(r) smartphone_Mt(6px)"
			return soup.find("div"					,  class_=class_	).find("span"	).text


if __name__ == "__main__":
						for symbol in "AAPL AMZN IBM GOOG MSFT ORCL".split():
												print(f'''Current {symbol:<4} stock price is {stock_price(symbol):>8}''')


